README.md

metadata

license: cc-by-nc-4.0
tags:
  - merge
  - mergekit
  - lazymergekit
  - abideen/MonarchCoder-7B
  - eldogbbhed/NeuralPearlBeagle
base_model:
  - abideen/MonarchCoder-7B
  - eldogbbhed/NeuralPearlBeagle
model-index:
  - name: NeuralMonarchCoderPearlBeagle
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: AI2 Reasoning Challenge (25-Shot)
          type: ai2_arc
          config: ARC-Challenge
          split: test
          args:
            num_few_shot: 25
        metrics:
          - type: acc_norm
            value: 68.52
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            value: 87.22
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 64.53
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 61.19
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 80.51
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 67.02
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=eldogbbhed/NeuralMonarchCoderPearlBeagle
          name: Open LLM Leaderboard

NeuralMonarchCoderPearlBeagle

NeuralMonarchCoderPearlBeagle is a merge of the following models using LazyMergekit:

• abideen/MonarchCoder-7B
• eldogbbhed/NeuralPearlBeagle

Goals

This is a TIES merge, formed from MonarchCoder-7b (A merge of Alpha Monarch and TessCoder) and NeuralPearlBeagle(which is a merge of mlabonne's NeuralBeagle14-7b and Pearl-7B-Slerp). It is a somewhat haphazard experiment to see if we can merge more math and coding capabilities into the already outstanding NeuralBeagle14-7b and still maintain the same positive chat abilities.

If you find this or my other merges useful, please consider sending a bit of BTC so I don't have to use Google Colab :D

BTC: bc1q8lc4mzdtdyz7fx44vaw3jn8qg6w4c3ypfxpdrv

ETH/POLYGON: 0x102a6fd187db8441d2cbead33ac70e87f382f114

🧩 Configuration

models:
  - model: abideen/MonarchCoder-7B
    parameters:
      density: 0.6
      weight: 0.5
  - model: eldogbbhed/NeuralPearlBeagle
    parameters:
      density: 0.8
      weight: 0.8
merge_method: ties
base_model: eldogbbhed/NeuralPearlBeagle
parameters:
  normalize: true
  int8_mask: true
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "eldogbbhed/NeuralMonarchCoderPearlBeagle"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	71.50
AI2 Reasoning Challenge (25-Shot)	68.52
HellaSwag (10-Shot)	87.22
MMLU (5-Shot)	64.53
TruthfulQA (0-shot)	61.19
Winogrande (5-shot)	80.51
GSM8k (5-shot)	67.02